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008			101111s2010 xxk| s |||| 0|eng d
020			_a9780857291486 _9978-0-85729-148-6
040			_cMX-MeUAM
050		4	_aQA297-299.4
082	0	4	_a518 _223
100	1		_aGriffiths, David F. _eauthor.
245	1	0	_aNumerical Methods for Ordinary Differential Equations _h[recurso electrónico] : _bInitial Value Problems / _cby David F. Griffiths, Desmond J. Higham.
264		1	_aLondon : _bSpringer London, _c2010.
300			_aXIV, 271p. 69 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Undergraduate Mathematics Series, _x1615-2085
505	0		_aODEs—An Introduction -- Euler’s Method -- The Taylor Series Method -- Linear Multistep Methods—I: Construction and Consistency -- Linear Multistep Methods—II: Convergence and Zero-Stability -- Linear Multistep Methods—III: Absolute Stability -- Linear Multistep Methods—IV: Systems of ODEs -- Linear Multistep Methods—V: Solving Implicit Methods -- Runge–Kutta Method—I: Order Conditions -- Runge-Kutta Methods–II Absolute Stability -- Adaptive Step Size Selection -- Long-Term Dynamics -- Modified Equations -- Geometric Integration Part I—Invariants -- Geometric Integration Part II—Hamiltonian Dynamics -- Stochastic Differential Equations.
520			_aNumerical Methods for Ordinary Differential Equations is a self-contained introduction to a fundamental field of numerical analysis and scientific computation. Written for undergraduate students with a mathematical background, this book focuses on the analysis of numerical methods without losing sight of the practical nature of the subject. It covers the topics traditionally treated in a first course, but also highlights new and emerging themes. Chapters are broken down into `lecture' sized pieces, motivated and illustrated by numerous theoretical and computational examples. Over 200 exercises are provided and these are starred according to their degree of difficulty. Solutions to all exercises are available to authorized instructors. The book covers key foundation topics: o Taylor series methods o Runge-Kutta methods o Linear multistep methods o Convergence o Stability and a range of modern themes: o Adaptive stepsize selection o Long term dynamics o Modified equations o Geometric integration o Stochastic differential equations The prerequisite of a basic university-level calculus class is assumed, although appropriate background results are also summarized in appendices. A dedicated website for the book containing extra information can be found via www.springer.com
650		0	_aMathematics.
650		0	_aElectronic data processing.
650		0	_aNumerical analysis.
650	1	4	_aMathematics.
650	2	4	_aNumerical Analysis.
650	2	4	_aNumeric Computing.
700	1		_aHigham, Desmond J. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780857291479
830		0	_aSpringer Undergraduate Mathematics Series, _x1615-2085
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-0-85729-148-6
596			_a19
942			_cLIBRO_ELEC
999			_c198378 _d198378